Before introducing the MLP regression algorithm, we provide a short
review of the TEBD algorithm so that computational comparisons to our
algorithm might be well understood. The TEBD algorithm facilitates the
time evolution (real or imaginary) of one-dimensional quantum systems
under local Hamiltonians.[1]} As such, it is naturally
expressed within the framework of matrix product states (MPS). The
time evolution is accomplished by generating and repeatedly applying
Suzuki-Trotter expansions of the time evolution operator
\(\exp {(-i\mathcal {H} T)}\) , up to any specified order. Given a
Hamiltonian with nearest-neighbor interactions and open boundary
conditions (OBC) over \(N\)  sites,
\(\mathcal {H} = \sum _{i=1}^{N-1} H_{i,i+1},\) 
